Mark Briers
Mark Briers publishes mostly in Artificial Intelligence, Statistics and Probability and Computer Networks and Communications, on topics such as Target Tracking and Data Fusion in Sensor Networks, Bayesian Methods and Mixture Models and Distributed Sensor Networks and Detection Algorithms.
- World rank
- #1,023,378 of 7,710,434 ranked researchers
- Rank in United Kingdom
- #82,805 of 367,258
- Works
- 45
- Citations
- 1.6k
- Citations per work
- 34.5
What does Mark Briers research?
Mark Briers's work is mostly in Computer Science (46%), Mathematics (17%), Medicine (5%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences2862.1%
- Computer Science2145.6%
- Mathematics716.5%
- Everything else1533.2%
- Health Sciences24.7%
- Medicine24.7%
- 1Artificial Intelligence32% of their works
- 2Statistics and Probability11% of their works
- 3Computer Networks and Communications9% of their works
- 4Modeling and Simulation6% of their works
- 5Epidemiology5% of their works
- 6Computer Vision and Pattern Recognition4% of their works
Research topics
- Target Tracking and Data Fusion in Sensor Networks
- Bayesian Methods and Mixture Models
- Distributed Sensor Networks and Detection Algorithms
- COVID-19 epidemiological studies
- Fault Detection and Control Systems
- Data-Driven Disease Surveillance
- Bayesian Modeling and Causal Inference
- Gaussian Processes and Bayesian Inference
Which keywords describe Mark Briers's research?
The keywords of their largest research topics: Bayesian Inference, Nonlinear Estimation, Particle Filters, Variational Inference, Machine Learning, Clustering, COVID-19 and Distributed Detection.
- Gaussian Processes
- Bayesian Networks
- Fault Detection
- Digital Epidemiology
- Modeling
- Distributed Detection
- COVID-19
- Variational Inference
- Nonlinear Estimation
- Bayesian Inference
- Particle Filters
- Machine Learning
- Clustering
- Mixture Models
- Wireless Sensor Networks
- Disease Surveillance
- Process Monitoring
- Causal Inference
- Sparse Regression
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 19 words, with their numbers
- Bayesian Inference303 topics
- Nonlinear Estimation191 topic
- Particle Filters191 topic
- Variational Inference112 topics
- Machine Learning92 topics
- COVID-1971 topic
- Clustering71 topic
- Distributed Detection71 topic
- Mixture Models71 topic
- Modeling71 topic
- Wireless Sensor Networks71 topic
- Digital Epidemiology51 topic
- Disease Surveillance51 topic
- Fault Detection51 topic
- Process Monitoring51 topic
- Bayesian Networks41 topic
- Causal Inference41 topic
- Gaussian Processes41 topic
- Sparse Regression41 topic
Where does Mark Briers work?
Mark Briers's main affiliation in the publication record is Qinetiq (United Kingdom), United Kingdom.
How many publications and citations does Mark Briers have?
OpenAlex counts 45 works and 1,552 citations for Mark Briers, an h-index of 17, ranking #1,023,378 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
Discussion
Ask a question or share a note about Mark Briers. Keep it to the research: no personal attacks, advertising or links. Any reader can report a post, which collapses it for everyone until it is opened.